• Title/Summary/Keyword: vegetative

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Fluvial Processes and Vegetation - Research Trends and Implications (하천과정과 식생 - 연구동향과 시사점)

  • Woo, Hyoseop;Cho, Kang-Hyun;Jang, Chang Lae;Lee, Chan Joo
    • Ecology and Resilient Infrastructure
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    • v.6 no.2
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    • pp.89-100
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    • 2019
  • We've reviewed existing studies on the interactions among vegetation, hydrology, and geomorphology in the stream corridors, adding one more factor of vegetation in the traditional area of hydro-geomorphology. Understanding of the interactions among those three factors is important not only academically but also practically since it is related intimately to the restoration of river corridor as well as management itself. Studies of this area started from field investigations in the latter part of the 20th century and focused on the flume experiments and then computer modelling in the 1990s and 2000s. Now, it has turned again to the field investigations of specific phenomena of the vegetative-hydrologic-geomorphologic interactions in detailed micro scales. Relevant studies in Korea, however, seem to be uncommon and far behind the international status quo in spite that practically important issues related directly to this topic have been emerged. In this study, we propose, based on the extensive literature review and authors' own knowledge and experiences, a conceptual diagram expressing the interactions among vegetation, flow (water), sediment, and geomorphology. Existing relevant studies in Korea since the 1990s are classified according to the categorization in the proposed diagrams and then briefly reviewed. Finally, considering the practical issues of riparian vegetation that have emerged recently in Korea, we propose areas of investigation needed in near future such as, among others, long-term and systematic field investigations and monitoring at multiple river corridors having different attributes on vegetative-hydrologic-geomorphologic interactions, including vegetative dynamics for succession.

Analysis of Spectral Reflectance Characteristics Using Hyperspectral Sensor at Diverse Phenological Stages of Soybeans

  • Go, Seung-Hwan;Park, Jin-Ki;Park, Jong-Hwa
    • Korean Journal of Remote Sensing
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    • v.37 no.4
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    • pp.699-717
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    • 2021
  • South Korea is pushing for the advancement of crop production technology to achieve food self-sufficiency and meet the demand for safe food. A medium-sized satellite for agriculture is being launched in 2023 with the aim of collecting and providing information on agriculture, not only in Korea but also in neighboring countries. The satellite is to be equipped with various sensors, though reference data for ground information are lacking. Hyperspectral remote sensing combined with 1st derivative is an efficient tool for the identification of agricultural crops. In our study, we develop a system for hyperspectral analysis of the ground-based reflectance spectrum, which is monitored seven times during the cultivation period of three soybean crops using a PSR-2500 hyperspectral sensor. In the reflection spectrum of soybean canopy, wavelength variations correspond with stages of soybean growths. The spectral reflection characteristics of soybeans can be divided according to growth into the vegetative (V)stage and the reproductive (R)stage. As a result of the first derivative analysis of the spectral reflection characteristics, it is possible to identify the characteristics of each wavelength band. Using our developed monitoring system, we observed that the near-infrared (NIR) variation was largest during the vegetative (V1-V3) stage, followed by a similar variation pattern in the order of red-edge and visible. In the reproductive stage (R1-R8), the effect of the shape and color of the soybean leaf was reflected, and the pattern is different from that in the vegetative (V) stage. At the R1 to R6 stages, the variation in NIR was the largest, and red-edge and green showed similar variation patterns, but red showed little change. In particular, the reflectance characteristics of the R1 stage provides information that could help us distinguish between the three varieties of soybean that were studied. In the R7-R8 stage, close to the harvest period, the red-edge and NIR variation patterns and the visible variation patterns changed. These results are interpreted as a result of the large effects of pigments such as chlorophyll for each of the three soybean varieties, as well as from the formation and color of the leaf and stem. The results obtained in this study provide useful information that helps us to determine the wavelength width and range of the optimal band for monitoring and acquiring vegetation information on crops using satellites and unmanned aerial vehicles (UAVs)